design, build, and deploy LLM‑powered and ML‑driven systems that operate at production scale
work on advanced data engineering pipelines
develop intelligent models for large‑scale data processing
contribute to next‑generation AI capabilities
build and optimize GenAI and LLM‑based solutions including prompt engineering, fine‑tuning, and model evaluation
develop applied machine learning models for large‑scale data processing, classification, enrichment, and automation
design and implement robust Python‑based pipelines using modern ML frameworks (PyTorch, TensorFlow, HuggingFace, etc.)
build scalable data engineering workflows, including ingestion, transformation, and feature pipelines
deploy and maintain production ML systems, ensuring reliability, observability, and performance
collaborate with cross‑functional teams to refine requirements, validate model outputs, and integrate ML components into production services
apply best practices for model lifecycle management, including versioning, monitoring, retraining, and cost‑efficient deployment
contribute to engineering standards, code reviews, and continuous improvement initiatives.

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or related field
5+ years of experience in ML engineering, data engineering, or software engineering with a strong ML focus
Ability to write clean, efficient, and maintainable code
Strong analytical mindset, problem solving skills, and attention to detail
Comfortable working in fast paced, agile environments
Strong expertise in GenAI / LLM engineering including hands on experience with modern LLM frameworks and tooling
Proven experience in applied machine learning, including model development, evaluation, and optimization
Advanced Python programming skills and deep familiarity with ML libraries and ecosystem tools
Solid understanding of data engineering foundations, including ETL pipelines, distributed processing, and data quality
Demonstrated experience deploying production ML systems (batch or real time)
Experience with cloud platforms (AWS preferred) for scalable ML and data workloads
Strong understanding of software engineering best practices, version control, CI/CD, and testing.

Senior GenAI / Machine Learning Engineer

Key skills